Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis

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Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis. / Bockmayr, Teresa; Erdmann, Gerrit; Treue, Denise; Jurmeister, Philipp; Schneider, Julia; Arndt, Anja; Heim, Daniel; Bockmayr, Michael; Sachse, Christoph; Klauschen, Frederick.

In: LAB INVEST, Vol. 100, No. 10, 10.2020, p. 1288-1299.

Research output: SCORING: Contribution to journalSCORING: Journal articleResearchpeer-review

Harvard

Bockmayr, T, Erdmann, G, Treue, D, Jurmeister, P, Schneider, J, Arndt, A, Heim, D, Bockmayr, M, Sachse, C & Klauschen, F 2020, 'Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis', LAB INVEST, vol. 100, no. 10, pp. 1288-1299. https://doi.org/10.1038/s41374-020-0455-y

APA

Bockmayr, T., Erdmann, G., Treue, D., Jurmeister, P., Schneider, J., Arndt, A., Heim, D., Bockmayr, M., Sachse, C., & Klauschen, F. (2020). Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis. LAB INVEST, 100(10), 1288-1299. https://doi.org/10.1038/s41374-020-0455-y

Vancouver

Bibtex

@article{ad88e1de770d448a826fb45ac977d5b6,
title = "Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis",
abstract = "Histomorphology and immunohistochemistry are the most common ways of cancer classification in routine cancer diagnostics, but often reach their limits in determining the organ origin in metastasis. These cancers of unknown primary, which are mostly adenocarcinomas or squamous cell carcinomas, therefore require more sophisticated methodologies of classification. Here, we report a multiplex protein profiling-based approach for the classification of fresh frozen and formalin-fixed paraffin-embedded (FFPE) cancer tissue samples using the digital western blot technique DigiWest. A DigiWest-compatible FFPE extraction protocol was developed, and a total of 634 antibodies were tested in an initial set of 16 FFPE samples covering tumors from different origins. Of the 303 detected antibodies, 102 yielded significant correlation of signals in 25 pairs of fresh frozen and FFPE primary tumor samples, including head and neck squamous cell carcinomas (HNSC), lung squamous cell carcinomas (LUSC), lung adenocarcinomas (LUAD), colorectal adenocarcinomas (COAD), and pancreatic adenocarcinomas (PAAD). For this signature of 102 analytes (covering 88 total proteins and 14 phosphoproteins), a support vector machine (SVM) algorithm was developed. This allowed for the classification of the tissue of origin for all five tumor types studied here with high overall accuracies in both fresh frozen (90.4%) and FFPE (77.6%) samples. In addition, the SVM classifier reached an overall accuracy of 88% in an independent validation cohort of 25 FFPE tumor samples. Our results indicate that DigiWest-based protein profiling represents a valuable method for cancer classification, yielding conclusive and decisive data not only from fresh frozen specimens but also FFPE samples, thus making this approach attractive for routine clinical applications.",
author = "Teresa Bockmayr and Gerrit Erdmann and Denise Treue and Philipp Jurmeister and Julia Schneider and Anja Arndt and Daniel Heim and Michael Bockmayr and Christoph Sachse and Frederick Klauschen",
year = "2020",
month = oct,
doi = "10.1038/s41374-020-0455-y",
language = "English",
volume = "100",
pages = "1288--1299",
journal = "LAB INVEST",
issn = "0023-6837",
publisher = "NATURE PUBLISHING GROUP",
number = "10",

}

RIS

TY - JOUR

T1 - Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis

AU - Bockmayr, Teresa

AU - Erdmann, Gerrit

AU - Treue, Denise

AU - Jurmeister, Philipp

AU - Schneider, Julia

AU - Arndt, Anja

AU - Heim, Daniel

AU - Bockmayr, Michael

AU - Sachse, Christoph

AU - Klauschen, Frederick

PY - 2020/10

Y1 - 2020/10

N2 - Histomorphology and immunohistochemistry are the most common ways of cancer classification in routine cancer diagnostics, but often reach their limits in determining the organ origin in metastasis. These cancers of unknown primary, which are mostly adenocarcinomas or squamous cell carcinomas, therefore require more sophisticated methodologies of classification. Here, we report a multiplex protein profiling-based approach for the classification of fresh frozen and formalin-fixed paraffin-embedded (FFPE) cancer tissue samples using the digital western blot technique DigiWest. A DigiWest-compatible FFPE extraction protocol was developed, and a total of 634 antibodies were tested in an initial set of 16 FFPE samples covering tumors from different origins. Of the 303 detected antibodies, 102 yielded significant correlation of signals in 25 pairs of fresh frozen and FFPE primary tumor samples, including head and neck squamous cell carcinomas (HNSC), lung squamous cell carcinomas (LUSC), lung adenocarcinomas (LUAD), colorectal adenocarcinomas (COAD), and pancreatic adenocarcinomas (PAAD). For this signature of 102 analytes (covering 88 total proteins and 14 phosphoproteins), a support vector machine (SVM) algorithm was developed. This allowed for the classification of the tissue of origin for all five tumor types studied here with high overall accuracies in both fresh frozen (90.4%) and FFPE (77.6%) samples. In addition, the SVM classifier reached an overall accuracy of 88% in an independent validation cohort of 25 FFPE tumor samples. Our results indicate that DigiWest-based protein profiling represents a valuable method for cancer classification, yielding conclusive and decisive data not only from fresh frozen specimens but also FFPE samples, thus making this approach attractive for routine clinical applications.

AB - Histomorphology and immunohistochemistry are the most common ways of cancer classification in routine cancer diagnostics, but often reach their limits in determining the organ origin in metastasis. These cancers of unknown primary, which are mostly adenocarcinomas or squamous cell carcinomas, therefore require more sophisticated methodologies of classification. Here, we report a multiplex protein profiling-based approach for the classification of fresh frozen and formalin-fixed paraffin-embedded (FFPE) cancer tissue samples using the digital western blot technique DigiWest. A DigiWest-compatible FFPE extraction protocol was developed, and a total of 634 antibodies were tested in an initial set of 16 FFPE samples covering tumors from different origins. Of the 303 detected antibodies, 102 yielded significant correlation of signals in 25 pairs of fresh frozen and FFPE primary tumor samples, including head and neck squamous cell carcinomas (HNSC), lung squamous cell carcinomas (LUSC), lung adenocarcinomas (LUAD), colorectal adenocarcinomas (COAD), and pancreatic adenocarcinomas (PAAD). For this signature of 102 analytes (covering 88 total proteins and 14 phosphoproteins), a support vector machine (SVM) algorithm was developed. This allowed for the classification of the tissue of origin for all five tumor types studied here with high overall accuracies in both fresh frozen (90.4%) and FFPE (77.6%) samples. In addition, the SVM classifier reached an overall accuracy of 88% in an independent validation cohort of 25 FFPE tumor samples. Our results indicate that DigiWest-based protein profiling represents a valuable method for cancer classification, yielding conclusive and decisive data not only from fresh frozen specimens but also FFPE samples, thus making this approach attractive for routine clinical applications.

U2 - 10.1038/s41374-020-0455-y

DO - 10.1038/s41374-020-0455-y

M3 - SCORING: Journal article

C2 - 32601356

VL - 100

SP - 1288

EP - 1299

JO - LAB INVEST

JF - LAB INVEST

SN - 0023-6837

IS - 10

ER -